Abstract

The ageing of the world population is an ineluctable process with major economic
implications. Whereas there is extensive research on macroeconomic effects
and on financial asset prices, there has been more limited systematic research
into the impact of demographic changes on financial asset volumes and financial
market structure more generally, as driven by age-related household saving
and asset allocation decisions. Our empirical work based on the experience
of 72 countries, viewed in the light of the existing literature, suggests that
demographic changes have had a detectable impact on financial structure. Ageing
tends to benefit bond markets relative to equity markets, while depressing
private saving and external balances, albeit not sharply reducing the overall
size of the financial sector. Continuation of such patterns during the coming
period of ageing have wide-ranging implications for policy-makers and market
participants.

1. Introduction

The ageing of the world population is an ineluctable process. It is anticipated that
by 2050 one in four people will be aged above 65 at the world level (UN Population
Division 2005). This pattern reflects both rising longevity and declining fertility
rates over the long term, as well as the exceptional size of the post-war ‘baby
boom’ generation. Such future trends will have major macroeconomic consequences.

The economic literature on demographics is in our view unbalanced. The link between
changing demographic structure and conjunctural trends at a macroeconomic level
has been widely studied (see for example, Kohl and O'Brien 1998; Turner
et al 1998; McMorrow and Roeger 2003; Batini, Callen and
McKibbin 2006). There is also an extensive literature on the impact of ageing
on pension systems and public finance (see Dang, Antolin and Oxley 2001
and McMorrow and Roeger 2002 for recent examples). Researchers in the United States
have put a considerable focus on links between demographic trends and financial
asset prices (see Poterba 2004 for a recent survey; also Davis and Li 2003
and Brooks, this volume). There has also been work on demographic impacts on
saving (see the review in Bosworth, Bryant and Burtless 2004). However, there
has been more limited systematic research into the impact of demographic changes
on individual financial asset volumes and financial market structure more generally.

Accordingly, in this paper we seek to fill the gap by reviewing the literature and
undertaking further investigation of the link between demographics and financial
market
structure.[2]
The paper is structured as follows. After assessing a number of stylised facts on
financial structure, we attempt to address the issue of the impact of ageing
on a number of levels.

First, we use a priori economic reasoning in terms of the life-cycle theory
of saving, bearing in mind likely developments in ageing. Second, we review
the existing literature on demographics and saving, to assess likely changes
in financial asset demand and asset prices (including the possible effect of
pension funding). Third, we seek to assess econometrically, using cross-country
data for up to 72 countries, the impact of ageing on existing financial systems
in terms of the volume of assets as well as private saving over the past 40
or so years. This assessment employs the World Bank Financial Structure Database,
for both advanced and emerging-market economies (EMEs). We seek to control
for a number of factors affecting financial structure (such as pension systems
and the level of economic development) in detecting demographic effects without
‘omitted variable bias’. In a final section, we estimate equations
for demographic effects on external balances using our panel dataset. Policy
aspects are highlighted in the conclusion.

2. The Evolution of Financial Systems

As background to assessing the impact of population ageing, it is essential to consider
how financial structures evolve as countries develop, and factors that influence
such development. It is important to understand what such normal financial
development entails so we do not mistake it for an effect of demographic developments,
perhaps due to omitting key variables from the econometric specification.

There is a widespread perception, backed by empirical observation, that financial
systems go through stages of development. For example, Rybczynski (1997) suggests
that one can distinguish bank, market and securitised phases. In the bank phase,
all finance is directed through banks, whereas securities markets and institutional
investors start to develop in the market phase and become dominant in the securitised
phase. Most EMEs are still in the bank phase, although the most advanced –
such as South Korea – are moving to a market phase (Davis 2005). Advanced economies are either in
the market or securitised phase (where ‘securitised’ implies a
growing importance of securities finance generally rather than just the packaging
of loans in the form of securities).

Stylised facts drawn from empirical observation suggest a somewhat more complex pattern
(see Allen and Gale 2000),
although the idea of these phases remains helpful. On average, as shown by Demirguc-Kunt
and Levine (2000), banks, non-banks and stock markets are larger, more active
and more efficient in richer countries. This is confirmed by background data
on financial structure provided in Tables 1 and 2 for EMEs and advanced economies,
respectively. Table 1 shows that for EMEs on average, private credit amounts
to the equivalent of 46 per cent
of GDP, while stock market capitalisation is equivalent to 44 per cent of GDP, private
bond stocks 16 per cent,
and public bond stocks are 25 per cent. In contrast, in advanced economies (Table 2)
the private credit ratio is 118 per cent of GDP, stock market capitalisation
72 per cent, and the outstanding stocks of both private and public bond markets
are equivalent to roughly 50 per cent of GDP.

Table 1: Financial Structure within EMEs – 2003

Country

Private credit by deposit money banks and other financial institutions to
GDP

Concentration (commercial bank assets. share of top 3)

Net interest margin

Stock market capitalisation to GDP

Private bond market capitalisation to GDP

Public bond market capitalisation to GDP

Argentina

0.118

0.468

0.052

0.624

0.100

0.056

Bolivia

0.486

0.511

0.056

0.173

na

na

Brazil

0.332

0.467

0.120

0.362

0.097

0.426

Bulgaria

0.224

0.468

0.044

0.063

na

na

Chile

0.750

0.591

0.051

0.864

0.194

0.274

Colombia

0.227

0.379

0.061

0.150

0.003

0.253

Costa Rica

0.287

0.591

0.081

0.111

na

na

Czech Republic

0.295

0.702

0.020

0.183

0.072

0.515

Dominican Republic

0.354

0.716

0.139

na

na

na

Ecuador

0.245

0.695

0.074

0.073

na

na

Estonia

0.292

0.982

0.036

0.021

na

na

Fiji

na

na

na

0.342

na

na

Honduras

0.380

0.489

0.081

na

na

na

Hong Kong, SAR

1.519

0.703

0.027

3.733

0.189

0.097

Hungary

0.378

0.540

0.056

0.174

0.034

0.409

Indonesia

0.219

0.534

0.048

0.204

na

na

Kazakhstan

0.189

0.632

0.057

na

na

na

Malaysia

1.327

0.429

0.025

1.414

0.530

0.363

Mexico

0.181

0.590

0.068

0.181

0.025

0.203

Pakistan

0.270

0.551

0.033

0.190

na

na

Panama

na

0.347

0.029

0.235

na

na

Peru

0.213

0.820

0.100

0.244

0.038

0.035

Philippines

0.349

0.430

0.033

0.396

0.001

0.280

Poland

0.281

0.419

0.040

0.153

na

0.291

Russian Federation

na

0.225

0.057

0.411

na

0.020

Singapore

1.132

0.964

0.012

1.360

0.231

0.389

Slovak Republic

0.350

0.674

0.034

0.071

na

na

Slovenia

0.392

0.606

0.032

0.207

na

na

South Korea

1.199

0.478

0.027

0.479

0.504

0.183

Sri Lanka

0.276

0.683

0.037

0.119

na

na

Thailand

0.957

0.522

0.026

0.564

0.156

0.210

Ukraine

0.197

0.490

0.053

0.075

na

na

Uruguay

0.503

0.661

0.066

0.017

na

na

Average

0.464

0.574

0.052

0.440

0.155

0.250

Source: World Bank Financial Structure Database

Table 2: Financial Structure within Advanced Economies – 2003

Country

Private credit by deposit money banks and other financial institutions to
GDP

Concentration (commercial bank assets, share of top 3)

Net interest margin

Stock market capitalisation to GDP

Private bond market capitalisation to GDP

Public bond market capitalisation to GDP

Australia

0.953

0.664

0.021

0.937

0.341

0.156

Austria

1.037

0.798

0.021

0.172

0.368

0.373

Belgium

0.757

0.830

0.022

0.501

0.394

0.971

Canada

0.989

0.543

0.027

0.885

0.214

0.561

Denmark

1.483

0.852

0.038

0.485

1.193

0.481

Germany

1.174

0.637

0.030

0.370

0.426

0.378

Iceland

1.000

0.975

0.021

0.748

1.326

0.158

Italy

0.825

0.405

0.026

0.375

0.439

0.847

Japan

1.046

0.331

0.017

0.601

0.444

1.207

Netherlands

1.515

0.833

0.018

0.876

0.566

0.446

New Zealand

1.136

0.608

0.024

0.361

na

0.278

Norway

0.952

0.919

0.021

0.368

0.242

0.173

Portugal

1.476

0.838

0.034

0.340

0.282

0.464

Spain

1.113

0.729

0.028

0.714

0.240

0.445

Sweden

1.022

0.967

0.031

0.776

0.401

0.411

Switzerland

1.559

0.903

0.015

2.080

0.403

0.287

United Kingdom

1.413

0.427

0.028

1.199

0.389

0.276

United States

1.736

0.311

0.039

1.175

1.126

0.443

Average

1.177

0.698

0.026

0.720

0.517

0.464

Source: World Bank Financial Structure Database

A further division is between countries at a similar level of development that are
market-oriented and those that are bank-dominated (see Table 3). Underlying
the relative importance of markets and banks are aspects relating to the role
of public information in markets as opposed to private information held by
banks, as well as banks' role in corporate governance. The classic distinction
is between the US and the United Kingdom on the one hand, and most continental
European countries and Japan on the other. In this context, developed economies
are themselves bimodal in their financial structure, with the market-oriented
Anglo-Saxon countries having larger-than-average securities markets and bank-dominated
countries having dominant banking sectors.

Table 3: Characteristics of Financial Systems

Country

Legal origin(a)

Bank-based(b)

Market-based(c)

Anti-director rights(d)

Argentina

F

1

0

4

Australia

CL

0

1

4

Austria

G

1

0

2

Belgium

F

1

0

0

Brazil

F

0

1

3

Canada

CL

0

1

5

Chile

F

0

1

5

Denmark

SC

0

1

2

Finland

SC

1

0

3

France

F

1

0

3

Germany

G

1

0

1

Greece

F

1

0

2

Hungary

G

1

0

3

India

CL

1

0

5

Ireland

CL

1

0

4

Italy

F

1

0

1

Japan

G

1

0

4

Malaysia

CL

0

1

3

Mexico

F

0

1

1

Netherlands

F

0

1

2

New Zealand

CL

1

0

4

Norway

SC

1

0

4

Portugal

F

1

0

3

Singapore

CL

0

1

4

South Africa

CL

0

1

5

South Korea

G

0

1

2

Spain

F

1

0

4

Sri Lanka

CL

1

0

3

Sweden

SC

0

1

3

Switzerland

G

0

1

2

Thailand

F

0

1

2

Turkey

F

0

1

2

United Kingdom

CL

0

1

5

United States

CL

0

1

5

(a) F: French; G: German; SC: Scandinavian; CL: Common Law (b) 1 = bank-based financial system (c) 1 = market-based
financial system (d) An index aggregating the shareholder rights,
formed by adding 1 when: (i) the country allows shareholders to mail their
proxy vote; (ii) shareholders are not required to deposit their shares
prior to the General Shareholders' Meeting; (iii) cumulative voting
is allowed; (iv) an oppressed minorities mechanism is in place; or (v)
when the minimum percentage of share capital that entitles a shareholder
to call for an Extraordinary Shareholders' Meeting is less than or
equal to 10 per cent (the sample median). The index ranges from 0 to 5.

Source: Impavido et al (2003)

Country status in terms of bank or market focus may be partly endogenous; Demirguc-Kunt
and Levine (2000) show that in developed economies, stock markets become more
active and efficient relative to banks, and that there is some tendency for
financial systems to become more market-oriented as countries become richer.
On the other hand, Schmidt, Hackethal and Tyrell (1999, 2001) argue that there
is path dependence, meaning that a bank-based system such as Germany will not
automatically develop into a market-based system, owing to the institutional
and legal structure that in a sense cements the bank-based structure in place.

A role for legal traditions in financial development and its link to market or bank
orientation has been considered by recent empirical work on law and finance.
This aspect appears to affect the relative size of banks and securities markets
separate from the stage of economic development. A classification of countries
by legal origin is also given in Table 3. La Porta, Lopez-de-Silanes and Schleifer
(1999) show that countries with a Common Law tradition, protection of shareholders'
rights, detailed accounting, low corruption and no explicit deposit insurance
tend to be market-based – and have large institutional investor sectors
– whatever their income level. In contrast, countries with a French Civil
Law tradition, poor protection of the rights of shareholders and creditors,
poor contract enforcement and accounting standards, restrictive banking regulation,
high corruption and inflation tend to have underdeveloped banks, markets and
institutional investors. The few countries with a German law tradition, which
offers strong protection for creditors, tend to have strong bank-based systems,
with small institutional investor sectors.

As regards historical trends, Rajan and Zingales (2000) show that financial development
has not been monotonic. The major OECD countries were on some measures more
financially developed in 1913 than 1980, with a significant reversal in financial
development and financial integration taking place between 1913 and 1950. A
tightening of regulation in the inter-war period led to a decline in the size
and importance of the financial sector relative to GDP. The imposition of such
‘structural regulation’ implied that the service provided to the
non-financial sector was sub-optimal and economic growth was hindered, with,
for example, low deposit rates and rationing of credit to households and small
companies. This illustrates the danger of complacency by law-makers in respect
of financial development. Meanwhile, financial liberalisation in the 1980s
and 1990s has of course tended to improve financial sector efficiency in securities
and banking, also leading to increased household borrowing, implying a cost
in terms of risk.

With this section as background we now turn to an assessment of the impact of ageing
on financial structure.

3. The Likely Impact of Ageing on Total Financial Assets

The main focus of ageing has to be on the relation between ageing and financial asset
demand for the personal sector, which is the ultimate holder of financial claims,
if one abstracts from foreign claims. Theory suggesting a link between an individual's
age, consumption and saving decisions originated with the permanent income
hypothesis (Friedman 1957),
and the later life-cycle hypothesis (Modigliani and Brumberg 1954; Ando and Modigliani
1963). For an overview of this literature, see Deaton (1992). Saving patterns
will in turn affect the aggregate size of the financial system, which is also
affected by features such as the presence of pay-as-you-go pension systems.

The permanent income hypothesis, while not explicitly basing saving on age, has the
insight that an individual's consumption is likely to depend on permanent
rather than current disposable income. People will only consume additional
income if they believe it will be sustained. Consequently, if increases in
their income are expected to be temporary, they will save rather then increase
their consumption. The underlying assumption is that people seek to avoid fluctuations
in their consumption when income fluctuates. Furthermore, when actual income
is below permanent income, that is, in retirement, they may decumulate wealth.

Following this insight, the life-cycle hypothesis of consumption suggests that, early
in one's life, consumption may well exceed income as individuals may be
making major purchases related to buying a new home, starting a family and
beginning a career. At this stage in life, individuals may borrow based on
their expected labour income in the future (human wealth), if financial markets
are sufficiently developed and liberalised. In mid-life, these expenditures
begin to level off while labour income increases. Individuals at this point
will repay debts and start to save for retirement in equities, bonds, pension
schemes, etc. At retirement, income normally decreases, and individuals may
start to dissave. This involves selling off some of their financial assets,
including pension fund decumulation.

Both theories of optimal consumption imply consumption will be smoothed out through
an individual's lifetime, with corresponding accumulation and decumulation
of financial assets. In the context of ageing, the life-cycle hypothesis is
a crucial background as it implies that personal saving will rise when the
high-saving age group grows, then fall as the population ages, and a larger
proportion of individuals enter the low- or negative-saving age groups.

As regards empirical evidence, at a macroeconomic time-series level Disney (1996)
notes that, consistent with the life-cycle hypothesis, saving rates tend to
decline in countries where there are a larger proportion of retired people.
The changes in saving rates lead to changes in demand for financial assets.
Econometrically, a strong effect of demographics on private saving is found
by many studies. Pioneering work in this area was by Fair and Dominguez (1991);
Attfield and Cannon (2003) apply their work to the UK using a vector-error-correction
approach. Masson, Bayoumi and Samiei (1995) find the total dependency ratio
to have a significant negative effect on private saving in a panel of both
advanced and developing countries, with an elasticity of −1. Later work
by Loayza, Schmidt-Hebbel and Servén (2000) suggests that this estimate
is lower at around −0.2. McMorrow and Roeger (2003) find an average elasticity
of −0.75 across existing studies.

Modigliani (1986) shows life-cycle savings follow a hump-shaped pattern where an
investor's asset holdings increase with age and decline after retirement.
Higgins (1998) estimates demographic effects via a third-order polynomial in
age and finds strong demographic effects; a similar exercise by Bosworth and
Keys (2004) finds a peak impact on saving from the age 40–55 cohort and
a negative effect from cohorts aged over 70. Al-Eyd, Barrell and Davis (2006)
test for demographic effects on consumption over and above the standard determinants
(that is, income and wealth), using the age cohorts 20–39, 40–64
and 65+ relative to the population in 15 countries (EU excluding Luxembourg
plus US). They find a strong positive effect on consumption from the 20–39
cohort, but no differential between the middle-aged and elderly as would be
expected if the latter draw down savings to pay for retirement. This in turn
may reflect pay-as-you-go pension schemes in most of Europe.

Whereas the above work focuses on time-series macroeconomic data, there is also a
large literature on life-cycle household saving using cross-sectional survey
data, notably in the US (see the survey in Bosworth et al 2004). A significant number of these studies find
that retired cohorts do not have negative saving. There is an apparent contradiction
between micro and macro evidence which would affect strongly the predictions
about personal saving when ageing and asset accumulation takes place.

Poterba (1998) suggests the life-cycle hypothesis cannot be proven by focusing on
average cross-section-based asset accumulation profiles for three reasons.
First, average figures are distorted by the wealthiest 10 per cent of households,
who hold approximately 70 per cent of financial assets. If equities are included,
this will raise the number to 90 per cent (see Poterba and Samwick 1995). Second,
micro data typically omit social security wealth and wealth in defined benefit
pension funds, which are important aspects of asset accumulation and decumulation
from the point of view of individual households. Third, there is a problem
in using cross-section data to evaluate the life-cycle hypothesis or project
asset demands, in the style of Yoo (1994) and Bergantino (1998) since they
mix age and cohort effects, as discussed by Poterba (2001). The associated
problems can be described using Equation (1) where Aαt
is individual asset holdings of age α at time t:

αa is the age-specific asset demand at age a,
βt
is the time-period-specific shift in asset demand and δt–a
is the cohort-specific effect for asset demand for those born in the period t−a.
‘Cohorts’ are a linear combination of age and time. With panel
or repeated cross-section data, it is possible to estimate two effects, but
it is impossible to estimate all three effects.

Poterba and Samwick (2001) estimate the effects of ageing using the US Survey of Consumer Finances data and allowing for this critique. They
find a hump shape for net worth but not for net financial assets, which level
off in old age. The levelling off of net financial assets could reflect precautionary
saving or a bequest motive (Hurd 1987; Bernheim 1991). On the other hand, Bosworth
et al (2004) suggest there may be intergenerational interactions
missed by even such micro studies, and problems of heterogeneity leading to
difficulty in aggregating micro studies.

Whereas our main focus is on personal saving and the related accumulation of financial
assets, it is important to add that as the population ages, the public sector
will tend to lower its saving, other things equal. This will in turn help to
drive external balances as discussed in Section 8. Such trends in public saving are largely
driven by the scale of the public pension system in light of ageing and the
means of financing adopted (for example, taxation versus debt finance). Recent
estimates include those in Dang et al (2001) and McMorrow
and Roeger (2002).
Debt finance would imply a greater fall in public saving. Rapid increases in the
proportion of the population over 65 (the dependency
ratio) combined with generous social security pension schemes are particularly
threatening. It is this aspect which is encouraging governments to scale down
public pension commitments and switch to funding.

4. The Likely Impact of Ageing on Demand for Financial Assets

While the life-cycle hypothesis focuses on overall household asset demand, empirical
evidence also suggests that households' desired portfolios of specific
asset classes would vary with age, which in turn would have a major effect
on financial structure. Hence, further work has related to the changing demand
for financial assets over the life-cycle. One underlying aspect of this relates
to implications for asset holdings of the life-cycle pattern of borrowing and
repayment, as well as pension accumulation. Another aspect of the underlying
theoretical view is that risk aversion may vary over the life-cycle, with individuals
seeking lower risk late in life (that is, shifting from equities to bonds).
Complementing this, the duration of assets would appropriately change over
the life-cycle, with long duration assets such as equities being more appropriate
for young workers saving for pension claims far in the future, and shorter
duration assets such as bonds being more relevant for older workers (Blake
1997). This would be particularly the case when (private) pensions are paid
out as annuities, which are generally backed by bonds. Note that such effects
relate on the one hand to directly-held assets but on the other to assets held
indirectly via pension funds. They may be partly offset if, as in many EMEs,
households are multigenerational, with labour income from younger households
in effect supporting pensioners.

Bergantino (1998), looking at cross-sections derived from the US Survey of Consumer Finances, finds that young households under 40
usually draw credit from the financial markets by taking out mortgages for
buying houses. Bergantino shows that households aged 40–60 tend to provide
credit to financial markets, via employer and personal pension accounts. Those
households which are over the age of 60 tend to withdraw from the financial
markets as a result of using accumulated assets to fund consumption at retirement.
Mankiw and Weil (1989) show that housing demand is high for those aged 25–40.
Thus, again, their borrowings tend to exceed their purchases of financial assets.

Goyal (2001), using aggregate stock market data, looks at the effect of cohort size
on outflows from the US equity market,
defined as the difference between the value-weighted stock market return (NYSE, AMEX
and NASDAQ), including dividends, and the percentage increase in stock market
capitalisation. He finds that outflows are related to a rise in the size of
the cohort aged 65 and over, and inflows are linked to the size of the cohort
aged 45–64, suggesting that a rise in the over-65 cohort will reduce
the net supply of equity finance.

Yoo (1994), using survey data, finds that demand for risky assets, bonds and equities
increases with age and decreases after individuals retire. Bergantino (1998)
shows that households with heads under the age of 35 generally have near-zero
ownership of bonds and stocks. However, he finds a divergence in stock and
bond holdings among older households. Ownership of stocks for those over 55
tends to decrease more rapidly than for bonds. He attributes this to possible
cohort effects and risk aversion. It is also noteworthy that financial assets
make up only 37 per cent of households' total assets, of which 15 per cent
are held directly in stocks. Thus, total household assets are mostly non-financial
assets, such as primary residences and vehicles, which are not the focus of
our current work.

These estimates are subject to the critique pointed out above of mixing cohort and
age effects for estimates of the life-cycle based on cross-sectional data.
On the other hand, Poterba (1998) shows that holdings of equities decline in
old age even allowing for age and cohort effects. Ameriks and Zeldes (2000),
who also correct for age and cohort effects using data from the US pension
fund TIAA-CREF, note a rapid increase in the proportion of households owning
equities, from 33 per cent in 1989 to 49 per cent in 1998, as the baby boom
generation increased in size. This is consistent with high equity holdings
by the high-saving middle-age group. But they also note that half of Americans
do not hold any wealth in the stock market.

Bodie and Crane (1997) look at the total asset holdings of individuals both inside
and outside retirement accounts and find that behaviour is in line with economic
theory and the ‘best advice’ of investment professionals. They
hold a proportion of cash that declines with wealth and a proportion of equities
that declines with age and rises with wealth. Consistent with this, Brooks
(2000) suggests that given the need to finance annuities, demand for equities
will fall more than demand for bonds as the population ages.

5. Impacts on Financial Asset Prices

A number of authors have sought to assess whether asset prices will also be put under
downward pressure in coming decades by declining saving in advanced economies
implicitly affecting the real interest rate or the risk premium. Particular
focus has been put on the concept of a ‘meltdown’ of equity prices
when the baby boom generation retires. The underlying issue for this paper
is the balance between price and quantity effects of changing demands for financial
assets. Arguably, in an efficient market excess demand for a certain type of
financial asset will lead initially to price rises, but in the longer term
to balance sheet adjustments that entail higher issuance of associated claims.

Schieber and Shoven (1994) suggest that given the correlation of ageing in OECD countries,
and the likely decumulation of defined benefit pension fund assets, there could
be widespread falls in asset prices, and associated high real interest rates.
Supporting this, Erb et al
(1997) find a positive correlation in the US between stock returns and the fraction
of the population aged 25–45 and 65+ (that is, a negative effect on prices),
while those aged 45–65 have a negative effect on returns. Looking at
a range of OECD countries and EMEs, they find a positive relation between stock
returns and the average age of the population. On the other hand, Brooks (this
volume), using an econometric approach, shows estimates suggesting at most
a modest decline in equity prices and possibly no decline at all.

Poterba (2001, 2004), although he acknowledges that standard models suggest that
equilibrium returns on financial assets will vary in response to changes in
population age structure, argues that the rapid meltdown hypothesis is inconsistent
with empirical survey data. Consumers decumulate assets at a less rapid rate
than the life-cycle hypothesis suggests. This is because the life-cycle model
takes no account of the bequest motive and lifetime uncertainty. Hence, although
asset demands rose to fuel the 1990s boom, future declines will be modest.
However, Abel (2001) using a rational expectations model which takes account
of the bequest motive, finds that stock prices are still expected to fall when
baby boomers retire, despite high projected asset demands owing to shifts in
the supply of capital in response to changes in its price.

Davis and Li (2003) give econometric evidence that demographics have had a significant
impact on US, panel and aggregated international stock prices and bond yields,
even in the presence of standard additional independent variables. As noted
by Poterba (2004, p 15), the Davis and Li study ‘… moves beyond
most of the previous work in including control variables for non-demographic
factors that may affect asset prices, such as the rate of economic growth,
the inflation rate, and the recent volatility of the equity market. The findings
are robust to the inclusion of these control variables’. In this context,
the age 40–64 cohort has a strong positive influence on equity and bond
prices, a support that would be removed as its share of the population declines.

Rather few studies have looked at relative demand for different assets with ageing
and its impact on prices. One exception is Brooks (2000) who, using a theoretical
overlapping generations model, focuses on the relation between ageing and the
demand for equities and bonds, and suggests that there will be excess demand
for bonds and excess supply of equities in coming decades, with a modest decline
in the returns on the retirement savings of baby boomers. He finds that the
bond yield rises from 4.5 per cent to 4.8 per cent as the baby boomers buy
equities, then falls to 4.1 per cent as they retire.

Consistent with the point we made above, Neuberger (1999) argues that the increase
and subsequent decrease in flows during ageing will be balanced by rises and
falls in equity issues, with little effect on prices and returns. This suggests
that there could nevertheless be a substantive impact on financial structure.

6. Impacts of Pension Funds on Financial Structure

As noted above, growth of pension funds is likely to accompany ageing and hence,
there is an important issue of whether pension reform more broadly affects
financial structure. An impact on saving, and hence financial asset volumes,
separate from demography would have to rely on the inability of the household
sector to offset forced saving via pension funds (for example, due to credit
constraints), and also – at a national level – that any rise in
personal saving is not offset by falling public saving.

As reviewed in detail in Davis (2005, 2006) and Davis and Hu (2006), there is evidence
that pension fund growth raises personal saving, but not one-for-one, as households
reduce discretionary saving to offset growth in pension claims. Effects on
saving are particularly marked where credit markets are imperfect (limiting
borrowing) or for lower-income individuals who are less creditworthy or who
do not have other assets to decumulate. Meanwhile, public dissaving may partly
or wholly offset rises in personal saving at a national level, especially if
the transition from pay-as-you go to funding is financed by debt issuance as
opposed to higher taxes. On the other hand, Lopez Murphy and Musalem (2004) using a panel
of 43 industrial and developing countries, find evidence suggesting that the
accumulation of pension fund financial assets might indeed increase national
saving, when these funds are the result of a mandatory pension program. The
boost to personal saving is thus greater than the dissaving of the public sector
due to reform. By contrast, national saving might be unaffected, when pension
funds are the result of a public program implemented to foster voluntary pension
saving.

Meanwhile, at the level of demand for individual financial assets, there is evidence
that growth of pension funds accompanies equity market development (Catalan,
Impavido and Musalem 2000), as well as entailing rises in the stock of private
and public bonds (Hu 2005; Impavido et al 2003). In terms of asset prices, pension fund growth
accompanies a decreased dividend yield and increased price-to-book ratio, as
well as lower equity price volatility implying a drop in the cost of capital
(Walker and Lefort 2002).

7. Econometric Analysis of the Impact of Demographics on Financial Structure

In light of the work cited above, in this section we undertake new tests of the hypothesis
that ageing affects financial structure. We assess demographic impacts both
for aggregates and also for ratios of financial assets. Data are for up to
72 countries from 1960–2002, of which 23 are OECD (that is, advanced)
economies, 36 are EMEs and 13 are transition
economies.[3]
Countries covered are listed in Appendix A.

We use GLS panel techniques with fixed effects. We follow authors such as Walker
and Lefort (2002) by adding extra explanatory variables such as inflation,
per capita income, urbanisation and openness (average of the ratios of imports
and exports to GDP) to estimate equations for financial structure and financial
development, so as to avoid the possibility of omitted variable bias boosting
the effect of the demographic variables. Openness we consider to be of particular
interest, given that it proxies the degree to which a country is integrated
in the global economy, which may in turn impact on the effect demographics
has on the domestic financial system.

On the other hand, following Arestis, Luintel and Luintel (2004) we do not include
some of the standard variables typically entered in cross-sectional cross-country
growth regressions such as years of schooling, as well as corruption, social
capital, inequality and the rule of law. We consider using panel data with
fixed effects will capture any relevant differences in financial structure
across countries. We estimate for all economies together, then for the EMEs
and advanced economies separately (transition economies are included with EMEs).

The dependent variables are firstly size variables, namely the ratios of bank loans
to GDP, M3 to GDP, equity market capitalisation to GDP and bond market capitalisation
to GDP, as well as the sum of loans, and bond and equity market capitalisation
to GDP (overall size indicator). This aggregate provides a rough total of domestic
financial assets, which are held by households either directly or indirectly
via financial institutions. Unfortunately, data on bond market capitalisation
are not widely available, so the observations for that variable and the total
size aggregate are limited. Note also that the equity market capitalisation
variable (and to a lesser extent the bond market capitalisation variable) mix
price and volume effects of ageing, as the data do not distinguish rises in
capitalisation due to new issues from those due to revaluations. Furthermore,
we do not have data on housing wealth for a wide range of countries, yet that
may be an important complement and determinant of financing patterns that can
vary with age.

We also assess a number of financial structure ratios, namely the economy-wide loan
to equity ratio, debt (loans plus bonds) to equity ratio and loan to
securities (bonds plus equities) ratio. Following the point made above, the
loan to equity ratio has the most observations. Finally, we consider two flow
ratios, namely the private saving to GDP ratio and (reported in the next section)
the external balance to GDP ratio.

Table 4 records
results for size variables for the full sample of up to 72 countries. From
the coefficient estimated on GDP per capita it is evident that most of the
size variables are correlated with economic development – countries with
higher living standards also have larger financial sectors, banking assets
and liabilities, and equity markets. Only the bond market result is opposite
to this. Equally, urbanisation tends to accompany financial development, although
the coefficient for equities is insignificant. Inflation is clearly inimical
to bond issuance, as would be expected, but not to overall financial sector
size or bank loan volume. More open economies tend to have larger banking sectors
and equity markets, although the overall size effect is insignificant. Note
that the overall size and bond results are based on quite small samples (37
countries and around 400 observations instead of 65 and over 1,000 for the
others) and hence may be less well-determined than the bank and equity results.

Turning to the demographic effects, a common feature is that the share of the over-65
cohort is significantly positively related to all the size variables. We need
to infer causality with caution however, as it may link partly to the fact
that countries with higher living standards have relatively larger populations
of pensioners. The relative magnitude of the coefficients on the age 40–64
and 65+ variables is of interest. For bonds, it is the over-65 cohort that
is most favourable to bond market development, consistent with the idea of
greater risk aversion of older people in work cited above. On the other hand,
for equities it is the age 40–64 cohort that is most favourable, consistent
with higher demand for equities among those in peak years of saving for retirement.
The coefficients for M3 and bank lending are similar for the two cohorts. Meanwhile,
the age 20–39 cohort is insignificant or negative for most of the equations,
consistent with low or negative financial saving by this cohort, but a high
demand for bank loans in the form of mortgages, where the lending equation
coefficient is positive.

To check for robustness, we add two lagged financial development variables, the pension
fund to GDP ratio and the bank lending to the private sector to GDP ratio (Table 4).
Most of the demographic coefficients are unchanged. Especially, the bulk of
the coefficients on the over-65 cohort variables are still positive and significant,
and the pattern for the age 40–64 cohort relative to the over-65s for
equities and bonds is as cited above. The exception is that the lending equation
has a negative sign for the younger cohorts with the extra variables. Pension
funding is shown to entail a larger stock of bonds and equities, and a smaller
banking sector, but a larger financial sector overall. Bank lending to the
private sector is positively related to overall size (with a smaller coefficient)
while there is also, unsurprisingly, a positive relationship with the banking
sector variables (where it is more or less a lagged dependent variable).

A further robustness check was to change the specification to one where the dependent
variable is a five-year average and the lagged variables are the ‘initial
conditions’ at the beginning of each 5-year period (Table 5). We
find that the demographic results are remarkably similar. Notably, we again
find the relatively greater effect of the age 65+ generation on bonds and the
40–64s on equities, consistent with risk aversion effects. The signs
on most of the non-financial variables are also robust.

As regards the size estimates for the EME and advanced economies (Table 6), results
are similar despite the differing living standards and levels of financial
development, which underpins the results for the full sample of countries.
There remain some differences, however. For EMEs, GDP per capita is favourable
for financial development except for bond markets, while for the advanced economies
there is a negative-sign relationship between GDP per capita and the size of
equity markets, possibly reflecting high living standards in some ‘bank
dominated’ countries. Bond market development for advanced economies
is not affected by GDP per capita, the level of which is of course fairly common
across advanced economies. In this context, note that in advanced economies,
the correlation between bonds and government debt is closer than in EMEs, where
much of government debt is a bank asset.

Urbanisation is positive and significant for all of the EME equations, but only for
overall size for the advanced economies. Again, urbanisation is comparable
across the advanced economies. Openness has a positive effect on financial
development for both sets of countries, although for the overall size regression
in EMEs and for overall size and M3 regressions in the advanced economies the
coefficients on openness are insignificant, and for the advanced economies
the coefficient for the bond market is negative – possibly reflecting
lesser fiscal discipline in the more closed economies. Inflation appears to
have a more consistent negative effect on financial development in the advanced
economies, where it has – for example – a significant negative
effect for bonds, equities and overall size. In contrast, it is positive for
overall size and loans in EMEs.

In terms of the demographic variables, the age 65+ cohort has a positive and significant
effect throughout, except for equities where it is insignificant for both subsets
of
countries.[4]
This is a more telling result than for the full set of countries, given that the
advanced economies and EMEs separately have more similar age distributions
than when they are pooled together. It suggests that there may indeed be a
positive effect of the elderly on the size of financial markets other than
equities, consistent with a pattern whereby they switch from equities to safe
assets, but the decline in net financial assets is not a sizeable one due to
precautionary saving or bequests as also suggested by Poterba and Samwick
(2001).[5]

Consistent with this suggestion, the dichotomy of results for equity and bond markets
across the age 40–64
and 65+ cohorts again applies, with only the 40–64 coefficient being significant
(and positive) for equity market development in both country groups. For the
bond market regression, the coefficient on the 40–64s cohort variable
is insignificant for EMEs while the coefficient on the 65+ cohort variable
is significant for both EME and advanced economy groups. The results confirm
that again, there is implied to be a relative switch by the elderly from equities
to bonds. Meanwhile, especially for the advanced economies, the coefficients
of these subgroups are comparable (positive and significant) for M3 and bank
lending, suggesting that liquid asset holding needs do not change with retirement.
Meanwhile the 20–39 cohort is shown to have a negative impact on M3 for
the advanced economies, but a positive effect on M3 and borrowing in the EMEs.
The contrast for M3 may reflect greater liquidity constraints in the EMEs.
Finally, the 20–39 cohort has a negative effect on overall size in both
cases, as do the 40–64s for EMEs.

Turning to estimates for financial structure ratios (Table 7), the
loan-equity equation has the most countries (67) and observations (1219). This
shows that economic development accompanies growth in securities markets relative
to banks, as witnessed by a negative sign on the GDP per capita and on urbanisation.
This is consistent with a shift to market orientation as economic development
proceeds, as discussed in Section 1. More open countries
also have a larger stock of equity funding relative to bank lending, consistent
with internationally integrated securities markets. Inflation is inimical to
equities as opposed to bank lending. The demographic variables are all negative
for this equation, but with the largest value for the 40–64 cohort, consistent
with larger relative demand for equities rather than bank liabilities for this
group. Meanwhile, for the loan-security ratio there are no significant demographic
effects, and for the debt-equity ratio the younger cohorts are shown (on the
smaller sample) to favour the development of debt markets (loans and bonds).
The equations with the financial development variables show similar patterns
for the demographic effects. A large pension fund sector is shown to accompany
a larger stock of equities relative to bank loans, as, interestingly, does
a larger banking sector. On the other hand, a larger volume of bank loans to
the private sector accompanies a higher loan-security ratio and economy-wide
debt-equity ratio.

Looking at the ratio results for the separate country groups (Table 8) briefly,
the loan-equity ratio is reduced strongly in advanced economies by the high
saving 40–64 cohort, who as shown in Table 7
encourage the development of equity markets more than bank loans. In the EMEs
it is the 20–39 and 65+ cohort that drive a fall in the loan-equity ratio
– the result for all countries in Table 7 was a mixture of these effects.

We finally highlight some results for private saving using demographic effects, as
shown in Table 9. Note
that this includes corporate as well as household saving. Given this area has
been widely researched (see Section
5), we do not put a major emphasis on these results. Nevertheless,
it is notable that strong and consistent demographic effects are detected for
all countries and both subgroups, with a range of financial structures. The
results are in turn consistent with the life-cycle hypothesis (although the
results do not prove
the life-cycle pattern holds for each individual cohort, since the aggregate macro
data show the average age behaviour of a range of cohorts).

In each case, the coefficients on the 20–39 and 40–64 cohort variables
are positive for private saving, and the 40–64 cohort always has a larger
coefficient. For EMEs, the coefficient on the 20–39 cohort variable is
positive and significant (and also for all countries) but in the advanced economies,
the 20–39 cohort variable is insignificant, which may reflect heavy borrowing
in financially liberalised economies, while the 20–39s face liquidity
constraints in EMEs. Meanwhile, the over-65 cohort has a consistently negative
and significant impact on saving, across all country groups. The contrast with
some of the positive results for financial asset accumulation may reflect the
existing stock of wealth that this cohort has built up, and positive revaluations
that will not be reflected in private sector saving. Finally, whereas the size
of the pension sector has no effect on private saving, there is a tendency
for countries with large bank lending to the private sector to have lower private
saving also.

Overall, we conclude from this preliminary empirical work that there are indeed detectable
demographic effects on financial structure, which can be expected to have important
implications for the future. Among other things, there is a switch from equities
to bonds between the 40–64 and 65+ cohorts, as well as a positive impact
of the older cohorts on banking and overall size of the financial sector. Saving
regressions show a strong positive effect for the 40–64 cohort and negative
for the 65+ one, consistent with other work in this area. So in an ageing economy,
a financial system may well become more bond- as opposed to equity-based, and
somewhat larger overall, while also facing declining inflows of saving.

This is an area which clearly warrants further research. Further work could assess
different specifications, notably using lagged dependent variables for the
financial structure variables, which would in turn necessitate using the Generalised
Method of Moments method for estimation.

8. Impacts of Ageing on Cross-border Financial Claims

In open economies, ageing will also impact on the external balance, depending on
the path of investment. In this context, most studies suggest that investment
rates will fall with ageing, which would temper the increase in external deficits
from lower saving. For example, Cutler et al (1990) suggest that total investment may fall with
ageing, given the reduced need for capital with a smaller workforce; they also
envisage a fall in the rate of return on capital from 6.7 per cent in 1990
to 3.5 per cent in 2025. Disney (1996) shows a significant negative relationship
between the elderly dependency ratio and fixed capital growth over 1977–1992
in 24 OECD countries. Blommestein (1998) again sees falling investment as likely
to occur as the labour force shrinks and the capital-labour ratio rises, depressing
returns to new investment. Higgins (1998) estimates that the cohort aged 15–24
has a peak positive effect on investment earlier than the peak positive effect on
saving due to the 30–45 aged cohort.

Bikker (1996) focuses directly on balance-of-payments effects of ageing and finds
that the effects in OECD countries may be to move the current account towards
a surplus as long as national saving is boosted by ageing, which seems possible
as long as the ‘baby boom’ generation remains at work. But once
people in this generation retire and begin to dissave, this could turn around.

In the light of this work, we undertook panel estimates for the external (current
account) balance, bearing in mind that it is a product of public as well as
private sector behaviour, and of investment as well as saving. These are also
reported in Table 9. Looking
first at the non-demographic effects, higher GDP per capita tends to push countries'
current accounts towards surplus, in the full group as well as the EMEs and
advanced economies separately. Rapid income growth tends to reduce current
account balances, but interestingly not for the advanced economies, where high
inflation pushes countries towards external deficits. As regards demographic
effects, the 20–39 cohort is not in any case a significant influence
on the external position. The 40–64 cohort tends to encourage a surplus
position, albeit not significantly for the advanced economies. This is plausible
in the light of high saving by this group, and also a likely beneficial effect
on government saving (higher tax receipts than expenditure needs). The 65+
generation is associated with a tendency to deficit in the external position
in all cases, consistent with lower private saving as discussed above as well
as pension and health expenditures by government with less offsetting tax inflows.
Finally, whereas the pension sector has no effect on the external position,
there is a tendency for countries with large bank lending to the private sector
to have deficits. This may of course reflect private investment financed by
such lending, as we now go on to discuss.

On balance, our results suggest that the pattern of ownership of financial claims
will shift relatively from advanced economies towards EMEs as the former age
more rapidly, although later ageing of the EMEs will tend to redress the balance.
These suggestions are supported by various macroeconomic projections as summarised
below.

9. Global Macroeconomic Projections

Illustrating the overall outcome of these ageing patterns, and giving further clues
about changes in financial structure with ageing, Turner et al
(1998) provided a simulation of the global effects of population ageing
(focusing both on changing population growth and age structure), using
the OECD's international dynamic general equilibrium macro-model MINILINK.
Reflecting the declining labour supply with ageing, economic growth is forecast
to decline to 0.25 per cent per annum in Japan, 1 per cent in Europe and 1.4
per cent in the United States
by around 2030. The slowdown in growth reduces investment needs directly. Furthermore,
a decline in the weight of the OECD in the world economy tends to shift OECD
current accounts towards a surplus (and hence
saving-investment balances) as non-OECD imports rise faster than OECD import
demand. The US,
Europe and Japan all generate current account surpluses of 2–3 per cent of
GDP up to 2025, as saving is initially boosted by the high proportion of high-saving
age groups while growth potential and hence investment weaken, thus building
up net external assets which help to buttress GNP. They thus build up ownership
of global financial claims, including those on EMEs.

On the other hand, eventual downwards pressures on public and private saving are
greater in the OECD than elsewhere, generating – in combination with
exchange rate appreciation – current account deficits for the three OECD
regions after 2025. The balance of ownership of global financial assets would
tend to switch at this point from OECD countries to EMEs. As world investment
in this simulation falls less than saving, world real interest rates are expected
to rise slightly, reinforcing the decline in investment. Reflecting differing
returns to capital, interest rates are higher in EMEs than in the OECD. The
authors note that higher saving in OECD countries could generate quite different
results, with lower real interest rates and consequently higher investment
and capital-labour ratios. There would also be greater net external assets,
boosting OECD GNP via inflows of interest, profits and dividends.[6]

McMorrow and Roeger (2003) concur that the EU and Japan will run current account
surpluses for some time, but expect the US to run ongoing deficits, reflecting
growth differentials and an assumption that the absorptive capacity of slow-ageing
EMEs is limited. Their projection, unlike that of Turner et al (1998) thus implies that the bulk of cross-border
claims will remain within the OECD region during that region's ageing phase.
They also note that such a continued concentration of capital flows within
the OECD is more likely to generate downward pressure on rates of return and
a risk of bubbles.

Finally, Batini et al (2006), using a dynamic intertemporal general equilibrium
model, again find slower growth and a current account deterioration for the
developed economies as the elderly run down assets in retirement. Interestingly,
more rapid productivity growth (in terms of catch-up with the US) can markedly
reduce the loss in growth from ageing, and related current account
balances.[7]

10. Conclusions

Summarising the paper, we noted initially that financial structure is intimately
related to the stage of development and legal structure of an economy. We then
highlighted that, in line with the life-cycle hypothesis, overall personal
saving is likely to rise then fall as ageing proceeds, thus impacting on the
size of financial claims and overlaying standard patterns of financial development.
Existing work also shows that ageing tends to accompany an initial shift into
securities followed by a relative shift from equities to bonds, as well as
a fall in household debt. There has been extensive work on securities prices
and ageing, much of which suggests that ageing will depress equity prices,
albeit modestly. Finally, most analysis suggests that ageing will accompany
rising current account surpluses in the advanced economies followed by deficits,
largely driven by changes in saving albeit also affected by demographic effects
on investment.

Our own empirical work suggests that demographic changes have had a detectable impact
on financial structure in both advanced economies and EMEs and will continue
to do so in the future if current relationships continue to hold. The similar
results for the two subgroups suggest that this may indeed be the case (as
advanced economies can be viewed as akin to EMEs at a later stage of ageing
and economic growth). Ageing tends initially to benefit equities (as the 40–64
cohort grows) but then as the 65+ cohort becomes predominant, it will benefit
bond markets relative to equity markets. Banking tends to benefit from large
cohorts aged 40–64 and 65+. Finally, a rise in the 65+ cohort also tends
to depress private saving and external balances, albeit not reducing the overall
size of the financial sector.

Policy-relevant issues, also necessitating further research, that are raised by the
effect of ageing on financial market structure include the following:

What will be the balance between price and quantity effects on financial markets
as the asset demands of the household sector evolve with ageing? If there
is a ‘meltdown’ will there be pressure on governments to accept
some of the burden of adjustment which would otherwise fall directly on holders
of defined contribution pension funds?

How should government financing evolve to meet the changing demands of the household
sector in terms of asset risk? Should they issue bonds linked to longevity
to overcome uncertainty over demographic changes?

How will companies cope with the changing demand for bonds and equities from the
household sector during ageing? Will there be an initial fall in debt-equity
ratios followed by a rise – leading to heightened bankruptcy risk at
a time when economic growth may also be sluggish? Or could asynchronous demand
for bonds and equities by advanced economy and EME households flatten out
this pattern?

Saving has seen a decline in many advanced economies after financial liberalisation,
as household sectors have undertaken heavy borrowing and relied on rising
asset prices (notably house prices) to maintain wealth-income ratios. Can
this continue as the population ages, and how will ageing, borrowing and house
prices interact?

Is it plausible that banking sectors will be relatively unaffected by ageing, as
implied by the empirical results?

Will there be difficulties in dealing with major cross border flows, initially from
advanced economies to EMEs and later reversed, which are also likely to drive
shifts in exchange rates and even financial instability (Davis 2002).
Why are such flows not occurring now? In other words, why are EMEs financing the
advanced economies via foreign exchange reserves? Can EMEs absorb the potential
volume of advanced economy claims in the short term (McMorrow and Roeger 2003)
and what are the economic and political implications of major shifts later
by EMEs into creditor status, when their economic development will be much
more comparable to that of the advanced economies than it is now? Will cross-border
EME asset demand help attenuate any pressures cited above for changes in asset
prices and composition of assets in advanced economies?

How should financial regulation adapt to the changing patterns of financial stocks
and flows foreshadowed in this work?

How will the changing structure of finance interact with growth in conjunction with
ageing? There is an extensive literature on finance and growth (see Beck and
Levine 2004 and Davis and Hu 2004 for example), while there is also emerging
evidence that ageing may affect growth (such as Davis 2006 who looks at a
possible impact on total factor productivity).

Will past patterns, which were estimated over periods when pension systems were more
pay-as-you-go-based,
change as pension funding becomes more important? Will the switch from defined benefit
to defined contribution pension funds change saving, and its composition between
debt and equity claims (for example, as risk-bearing households under defined
contribution schemes become more cautious)?

Appendix A: List of Countries Utilised in Econometrics

EMEs

Transition economies

Advanced economies

Algeria

Bulgaria

Australia

Argentina

China

Austria

Bolivia

Croatia

Belgium

Brazil

Czech Republic

Canada

Chile

Hungary

Denmark

Colombia

Kazakhstan

Finland

Costa Rica

Latvia

France

Dominican Republic

Poland

Germany

Ecuador

Romania

Greece

Egypt

Russian Federation

Iceland

El Salvador

Slovak Republic

Ireland

Fiji

Ukraine

Italy

Honduras

Vietnam

Japan

Hong Kong, SAR

Luxembourg

India

Netherlands

Indonesia

New Zealand

Israel

Norway

Jordan

Portugal

Malaysia

Spain

Mexico

Sweden

Morocco

Switzerland

Nigeria

United Kingdom

Pakistan

United States

Panama

Paraguay

Peru

Philippines

Singapore

South Africa

South Korea

Sri Lanka

Thailand

Tunisia

Turkey

Uruguay

Venezuela

Footnotes

E Philip Davis is Professor of Economics and Finance, Brunel University, Uxbridge,
Middlesex, UB8 3PH, United Kingdom and Visiting Fellow, NIESR, Dean Trench
Street, London SW1. e-mails: philip.davis@brunel.ac.uk and e_philip_davis@msn.com.
I thank Yu-Wei Hu for the provision of data used in the empirical work reported in
this paper (see Hu 2005) and also participants in a seminar at Brunel University
and at the G-20 conference itself for helpful comments.
[1]

Financial market structure can be viewed from several angles, namely in terms of
overall size, by institutional sectors (for example, household, corporate,
banks and institutional investors) and by instrument (for example, bonds,
equities and deposits), as well as on a domestic and international level.
A complication is that detailed ‘national-balance-sheet’ data
on all of these aspects is only available for a small number of advanced
economies. However, a wider range of countries are covered by the World Bank
Financial Structure Database, notably in terms of volumes of equities, bonds
and bank assets that we utilise here.
[2]

Data are largely from World Bank's World Development Indicators
and the Financial Structure and Economic Development Database. I am indebted to Yu-Wei
Hu for use of the data he has collected.
[3]

We note that the lack of significance of equities for the over-65 variable rules
out the possibility that results for EMEs are driven by a correlation of
longevity with overall development.
[4]

Of course, the foreign sector may also be an important concurrent investor in these
assets, notably in small open economies.
[5]

The return on such investments will depend on factors such as labour and product
market reforms in the EMEs as well as the overall size of such flows from
the OECD (if the flows are sizeable enough, they will depress the return
to capital in the EMEs).
[6]

See Davis (2006) for a review of existing work and new estimates of the impact of
age structure on productivity, as well as that of pension funding.
[7]

Poterba JM and AA Samwick (2001), ‘Household Portfolio Allocation over the
Life Cycle’, in S Ogura, T Tachibanaki and DA Wise (eds), Aging Issues in the United States and Japan, University of Chicago
Press, Chicago, pp 65–103.

Rajan RC and L Zingales (2000), ‘The Great Reversals: The Politics of Financial
Development in the 20th Century’, OECD Economics Department Working paper No
265.